A Theory of Rolling Horizon Decision Making

Annals of Operations Research, Vol. 29, No. 1, December 1991

29 Pages Posted: 30 Jan 2008 Last revised: 7 May 2014

See all articles by Suresh Sethi

Suresh Sethi

University of Texas at Dallas - Naveen Jindal School of Management

Gerhard Sorger

University of Vienna - Faculty of Business, Economics, and Statistics

Abstract

In this paper, we develop a theoretical framework for the common business practice of rolling horizon decision making. The main idea of our approach is that the usefulness of rolling horizon methods is, to a great extent, implied by the fact that forecasting the future is a costly activity. We, therefore, consider a general, discrete-time, stochastic dynamic optimization problem in which the decision maker has the possibility to obtain information on the uncertain future at given cost. For this non-standard optimization problem with optimal stopping decisions, we develop a dynamic programming formulation. We treat both finite and infinite horizon cases. We also provide a careful interpretation of the dynamic programming equations and illustrate our results by a simple numerical example. Various generalizations are shown to be captured by straightforward modifications of our model.

Keywords: rolling horizon, stochastic dynamic optimization, dynamic programming, forecast horizons, decision horizons, planning horizons, forecasting

JEL Classification: C61, M10

Suggested Citation

Sethi, Suresh and Sorger, Gerhard, A Theory of Rolling Horizon Decision Making. Annals of Operations Research, Vol. 29, No. 1, December 1991, Available at SSRN: https://ssrn.com/abstract=1087813

Suresh Sethi (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

800 W. Campbell Road, SM30
Richardson, TX 75080-3021
United States

Gerhard Sorger

University of Vienna - Faculty of Business, Economics, and Statistics ( email )

Vienna, A-1210
Austria

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
178
Abstract Views
1,644
Rank
304,866
PlumX Metrics